Which GPU should I use on Google Cloud Platform (GCP)

Right now, I'm working on my master's thesis and I need to train a huge Transformer model on GCP. And the fastest way to train deep learning models is to use GPU. So, I was wondering which GPU should I use among the ones provided by GCP? The ones available at the current moment are:

• NVIDIA® A100
• NVIDIA® T4
• NVIDIA® V100
• NVIDIA® P100
• NVIDIA® P4
• NVIDIA® K80

It all depends on what are the characteristics you're looking for.

First, let's collect some information about these different GPU models and see which one suits you best. You can use this link to track the GPUs performance, and this link to check the pricing of older GPU cores, and this link for the accelerator-optimized ones.

I did that and I created the following table

Updated (June 2024)

† The mimimum amount of GPUs to be used is 8.

‡ price includes 1 GPU + 12 vCPU + default memory.

In the previous table, you see can the:

• FP32: which stands for 32-bit floating point which is a measure of how fast this GPU card with single-precision floating-point operations. It's measured in TFLOPS or *Tera Floating-Point Operations... The higher, the better.
• Price: Hourly-price on GCP.
• TFLOPS/Price: simply how much operations you will get for one dollar.

From this table, you can see:

• Nvidia H100 is the fastest.
• Nvidia Tesla P4 is the slowest.
• Nvidia A100 is the most expensive.
• Nvidia Tesla T4 is the cheapest.
• Nvidia Tesla L4 has the highest operations per dollar.
• Nvidia Tesla A100 has the lowest operations per dollar.
• Nvidia K80 went out-of-support as of May 1 2024.

And you can observe that clearly in the following figure:

[]

I hope that was helpful!